Statewide Applications by Gender
The following table summarizes female and male application data for the state as a whole and for the top fifty institutions:
Table 4 - Statewide and Top 50 Application Data|
Female Apps |
% of All Apps |
Male Apps |
% of All Apps |
Fem:Mal Ratio of Apps |
|
|
State Total |
22,006 |
19.7% |
89,443 |
80.3% |
0.25 |
|
Top 50 Total |
8,031 |
19.8% |
32,453 |
80.2% |
0.25 |
From APPENDIX I, Table 26
State and top 50 male and female application levels, and the corresponding female-to-male application ratios, appear consistent.
The most noteworthy statistic is the female-to-male application ratio. For every woman who applied for a home purchase mortgage loan in 1994, four men applied. On its face, this suggests that there is an access differential for women. However, this ratio appears to be in proportion with available census information showing that there is one female-headed family for every five married-couple families.
Table 5 - New Jersey Household Data|
State |
Female Householder |
Married Couple Family |
Ratio |
|
New Jersey |
328,435 |
1,612,285 |
.20 |
(From APPENDIX II)
The census ratio is rough—it does not account for New Jersey’s 756,529 non-family households—but it does suggest that the one to four female-to-male application ratio does not provide dramatic evidence of a gender-influenced differential. The female-to-male application ratio and census household information combined might indicate a noteworthy, gender-influenced trend: in married couple family households, it appears that men are more likely to be the lead home purchase mortgage applicant.
Although state and top 50 female-to-male application ratios are consistent, lender behavior varies among the top 50 institutions. Figure 1 details the distribution of female-to-male application ratios among the top 50 institutions (see APPENDIX I, Table 27 for tabular data).
Figure 2 - Female to Male Application Ratios
Table 6 suggests that the medium-to-large institutions (receiving more than 600 applications) are clustered around the mean female-to-male application ratio. Very small institutions, both those with low and high female-to-male application ratios, are represented heavily among the outliers: eight of the sixteen low-application ratio institutions (<.2) received fewer than 300 total applications. The same is the case for four of the twelve high-application ratio institutions (>.3). Because of the size of these institutions, and with no data on their branch locations, it would be inappropriate to speculate about the cause of their high or low-ratios—these ratios may vary from year to year.
Table 6 - Summary of F:M Application Ratios for Medium-to-Large Institutions|
F:M App Ratio |
All Applications |
Average Applications |
Total # of Institutions |
Institutions Receiving Over 600 Apps |
|
Low Ratio<.20 |
13,066 |
817 |
16 |
4 |
|
Ratio >=.20 and >=.30 |
18,541 |
843 |
22 |
10 |
|
High Ratio >.30 |
8,877 |
740 |
12 |
4 |
(From Table 11)
There are a number of larger institutions among the outliers. Their performance vis-à-vis women’s applications may point to institution wide practices which encourage or discourage women applicants.
Table 7 - Large Institutions with Low F:M Application Ratios (<.2)
|
Institution Name |
All Applications |
Female Applications |
Male Applications |
F:M Application Ratio |
|
Summit Bank |
2,577 |
379 |
2,198 |
0.17 |
|
Hudson City Savings Bank |
2,454 |
373 |
2,081 |
0.18 |
|
Provident Savings Bank |
1,337 |
206 |
1,131 |
0.18 |
|
Chase Manhattan Mortgage Corp. |
4,177 |
670 |
3,507 |
0.19 |
(From Table 11)
Table 8 - Large Institutions with High F:M Application Ratios (>.3)|
Institution Name |
All Applications |
Female Applications |
Male Applications |
F:M Application Ratio |
|
Fleet Real Estate Funding |
1,615 |
394 |
1,221 |
0.32 |
|
United Jersey Bank |
2,396 |
599 |
1,797 |
0.33 |
|
Chemical Bank New Jersey NA |
1,293 |
398 |
895 |
0.44 |
(From Table 11)
The large lenders in Table 7 are not performing up to industry standards in terms of attracting women applicants. However, these large lenders are receiving more female applications (relative to their own male applications received) than their peers. While it is important to note these institutions for their high- or low-application ratios—the low-ratio institutions should be subject to more scrutiny for their failure to attract female applicants—application and origination data combined provide a more complete picture of a lenders’ performance vis-à-vis women. A geographic analysis would also enhance our understanding of application ratios: the low-ratio banks may be located in areas comprised of mostly married couple households. These households appear less likely to have a female as lead applicant, and the low bank female-to-male application ratios may reflect this. ( From APPENDIX I, Table 27 .)
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